The construction process of the improved data fusion model. by Tang Ruipeng (20141334)

Subjects:

Construction process of RF. by Xini Fang (20861990)

Subjects:

Brain-inspired algorithm “cocktail party” listening data for individuals with hearing loss by Alex Boyd (20911316)

SSA fitness curve. by Jin Wang (29560)

Elements: Kingfisher: Storage Management for Data Federations (CSSI PI Meeting 2025) by Brian Bockelman (5128082)

Data collision free processing unit. by Ayesha Waris (21368446)

Effect of post-processing threshold and algorithms performance on the species composition estimation. by Valentine Fleuré (12822137)

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Performance of SiamFC_TDA algorithm and comparison algorithm on UAV123. by Yi Tao (178829)

Performance of SiamFC_TDA algorithm and comparison algorithm on TC-128. by Yi Tao (178829)

Fitting effect of different distribution parameters. by Jiayuan Wang (3765376)

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Processed data for figures. by Jin Zhang (53297)

Flow of data processing and preparation. by Xuan Wang (55634)

“…The gathered properties are processed using normalized techniques to convert unstructured data into structured data, which directly improves the overall prediction accuracy. …”

Genetic algorithm iteration data chart. by Wenguang Li (6528113)

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Performance of SiamFC_TDA algorithm and comparison algorithm on UAV20L. by Yi Tao (178829)

Ricker seismic profile. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Noise reduction on testing sets from STEAD. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

SNR comparison of real-field seismic profile. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

The flowchart of GWO-VMD method. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

The 147th single trace. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Process of facial feature extraction and recognition method based on ipca algorithm. by Lu Lin (201289)